Results from our own research over 15 years shows that what a patient gets (in terms of diagnosis, medications, tests ordered and management decisions) is as much a function of who the patient is (age, gender, race/ethnicity), who the provider is (gender and level of experience) and where the care is delivered (private vs. public facility, practice culture, geographic location, or health care system), as it is of what signs and symptoms are actually presented. Further progress in the field requires moving beyond endless documentation of differences and toward understanding the quality of decision making-why these differences persist. Our proposed study addresses priorities identified across NIH program announcements on mental illness stigma, health disparities, and mechanisms linking physical and mental disorders (PA-07-027, PA-07- 212, IOM reports Crossing the Quality Chasm and Unequal Treatment, and a recent NIMH meeting, Translational Research: Bridging Basic and Applied Perspectives [May 2006]). The research proposed here would extend previous work by examining how clinical decision making (CDM) processes operate in the case of a physical illness (diabetes) that is co-occurring with potentially stigmatizing mental illness conditions. Estimating the influence of nonmedical influences on CDM under these circumstances will help us understand stigma production and the specific cues from patients that trigger differential treatment decisions (e.g., diagnostic labels versus observable behavioral differences relative to a non-stigmatizing control comorbidity). An experimental design will further allow us to measure variation in clinical behavior according to patient and provider characteristics, while our use of think-aloud qualitative data will allow for in-depth analyses of how physicians make decisions. In order of priority, specific aims include: AIM 1: To measure how the presence of one of 4 comorbid conditions depicting varying levels of stigma (schizophrenia with bizarre affect; schizophrenia with normal affect; depression, and eczema) influence clinical management of the videotaped vignette scenario. AIM 2: To use think-aloud data and qualitative analyses to understand the underlying cognitive reasoning and mental processes that produce the clinical decisions we observe. AIM 3: To estimate the influence of patient attributes (race/ethnicity, gender, and age) on clinical management of the videotaped vignette scenario. AIM 4: To estimate the influence of physician characteristics (age/clinical experience and gender) on clinical management of the videotaped vignette scenario. AIM 5: To measure the influence of organizational features of the health care system (e.g., size and ownership of practice, practice culture) as covariates with respect to the clinical scenario. Findings from this research will have practical implications for translational research (moving research from bench to bedside), health policy, and medical education and are discussed. PUBLIC HEALTH RELEVANCE: This proposed study uses a video vignette factorial experiment and qualitative think-aloud data to study the influence of (1) potentially stigmatizing comorbidities (schizophrenia with normal affect, schizophrenia with bizarre affect, depression, and eczema); (2) patient; (3) physician; and (4) healthcare system attributes on diagnostic and treatment decisions for a case of diagnosed diabetes.